Senior Data Scientist - Energy Analytics

Placements24; South Africa; On-site; ZAR 1,200,000 - 1,900,000; Full time

Benefits offered by this job

Competitive salary

Equity opportunity

Medical & retirement benefits

Professional development budget

Job summary

Placements24 in Paarl seeks a Senior Data Scientist specializing in Energy Analytics to leverage large energy datasets, build predictive models, and develop data-driven solutions that optimize energy generation, distribution, and consumption.

The role requires a PhD or Master’s in a quantitative field, 5+ years of experience, and proficiency with Python or R, ML libraries, and big data on cloud platforms.

Qualifications

• PhD or Master's in a quantitative field.
• Minimum 5 years of data science experience in energy.
• Proficiency in Python or R and ML libraries.
• Experience with big data tech (Spark/Hadoop) and cloud platforms (AWS/Azure/GCP).

Responsibilities

• Develop ML models for energy forecasting, anomaly detection, and demand prediction.
• Analyze energy datasets to identify trends, patterns, and insights for business strategy.
• Design and build data pipelines for large-scale energy data collection and processing.
• Collaborate with domain experts, engineers, and stakeholders to define analytical problems and deliver solutions.
• Communicate findings and recommendations through data visualizations and presentations to diverse audiences.

Skills

Energy analytics

Machine learning

Python

R

Statistics

Data engineering

Communication

Education

Ph.D. or Master's in Data Science or related field

Tools

Spark

Hadoop

TensorFlow

PyTorch

AWS

Azure

GCP

Job description

About the Role

Our client is seeking an innovative and experienced Senior Data Scientist specializing in Energy Analytics to join their advanced analytics team in Paarl. You will be responsible for leveraging large datasets from across the energy value chain to uncover insights, build predictive models, and develop data-driven solutions that optimize energy generation, distribution, and consumption. This role requires a strong foundation in statistics, machine learning, and data engineering, combined with a deep understanding of the energy sector's unique challenges and opportunities. You will work with cutting-edge tools and technologies to transform raw data into actionable intelligence that drives strategic business decisions and enhances operational efficiency.

Key Responsibilities

• Develop and implement machine learning models for energy forecasting, anomaly detection, and demand prediction.
• Analyze complex energy datasets to identify trends, patterns, and insights that inform business strategy.
• Design and build data pipelines for collecting, cleaning, and processing large volumes of energy-related data.
• Collaborate with domain experts, engineers, and business stakeholders to define analytical problems and deliver solutions.
• Communicate findings and recommendations through compelling data visualizations and presentations to both technical and non-technical audiences.

Requirements

• Ph.D. or Master's degree in Data Science, Statistics, Computer Science, Physics, or a related quantitative field.
• Minimum of 5 years of professional experience in data science, with a proven track record in the energy industry.
• Proficiency in programming languages such as Python or R, and relevant libraries (e.g., scikit-learn, TensorFlow, PyTorch).
• Experience with big data technologies (e.g., Spark, Hadoop) and cloud platforms (e.g., AWS, Azure, GCP).
• Strong analytical, problem-solving, and communication skills for driving insights in Paarl.

Benefits

• Exceptional salary and potential for equity or profit-sharing.
• Comprehensive medical, dental, and retirement benefits.
• Generous budget for professional development, conferences, and training.
• Opportunity to work on impactful projects at the forefront of energy innovation.
• A dynamic and intellectually stimulating work environment.